Addressing Performance Variability
Outdated Process Series
Previous articles in this series discussed the challenges of identifying outdated and inefficient processes. This article will concentrate on performance variability as one of the indicators of an inefficient process and will look at some ways to effectively address it.
When it comes to business, variability is generally not welcome. It prevents us from creating accurate forecasts, makes us keep extra inventory on hand, leads us to engage more resources than we need, and thwarts long-standing plans. In other words, variability causes inefficiency.
Many kinds of variability are unavoidable but can be managed with analytic and quantitative approaches, like the Erlang staffing model. There are, however, types of variability which can and should be controlled. Performance variability, for example, which can have a very significant impact on efficiency and profitability, squarely belongs in the controllable category.
What is Performance Variability?
Performance variability occurs when different levels of efficiency are observed among similar roles or processes under similar conditions. This could refer to employees of the same skill level performing very differently, or similar processes yielding significantly different results, or two or more identical pieces of equipment showing varied throughput and/or quality.
Identifying Performance Variability
The first step in identifying performance variability is recording the variance in performance through observation or analysis. Next, any and all external factors which could cause the variance in results should be accounted for.
Once external factors are ruled out, and it’s established that conditions are, in fact, similar, analysis should be redirected to the root causes of the variability. A closer and more detailed look needs to be taken at each individual, process, or piece of equipment in question.
Addressing Performance Variability
When dealing with equipment, performance variability is straightforward and can usually be corrected by repair or replacement, and then avoided in the future with a proper maintenance program. Performance variability involving people is far more complex.
Let’s look at some root causes of employee performance variability, along with some actions that managers can take to rectify the situation:
- Difference in skills: Sometimes it’s assumed that two or more employees have the same skill level, but no formal skills evaluation was ever put in place. By introducing tools like an employee skills matrix, it’s possible to verify skillsets and address any gaps with training;
- Unclear expectations: Often, manager don’t clearly communicate expectations to front-line employees. Providing managers with a certain amount of coaching and setting KPIs used in active management usually resolve the variability
- Fear of losing service levels: This is prevalent in environments like call centers, where the drive to meet service levels comes at the expense of everything else. Coaching for managers and front-line staff, as well as smart KPIs can lead to a philosophy shift that resolves the variability by acknowledging that excellent customer service can be offered in an efficient manner.
- Opportunistic behaviour: Sometimes the hurdles to employee performance are far more individual, like a personal problem or a lack of underlying motivation. Intervention by a good active manager can identify and rectify this cause of variability and help put performance back to desired levels.
- Lack of fit: Once all other options are exhausted, the only answer left is usually lack of fit. To resolve this, management can consider reassigning a particular resource to a different role, or redistributing responsibilities to other resources.
Identifying and addressing performance variability in people can be complex, and often requires an external and experiences perspective to effectively evaluate processes, systems, and behaviours.
Click here to find out more about Trindent’s approach and how we can help your organization address performance variability.